Forecast of car park utilisation
Information provision, forecasting and analysis of the real-time occupancy of car parks on the Bildungscampus to avoid congestion and develop alternative space utilisation concepts
Duration: since June 2020
© Fraunhofer IAO
Contact person
Vincent Philipp Göbels
E-Mail: vincent-philipp.goebels [at]
iao.fraunhofer.de
Phone: +49 711 970-5268
Together with various stakeholders on the Bildungscampus, future visions for the smart campus of tomorrow were developed as part of the Smart Campus Initiative. In the process, students noted that there are often long queues in front of the multi-storey car parks and the associated unnecessarily high pollutant emissions due to vehicle congestion. Due to the current lockdown, car parks are currently mostly empty, which brings new challenges but also potential.
The aim of the project is to record and forecast the occupancy patterns of the car parks on campus as accurately as possible in order to be able to offer these to stakeholders as an information service for finding parking spaces on the one hand and to be able to organise the use of the car park spaces flexibly and efficiently on the other.
First, an interface to the car park occupancy data is provided. This can be used to retrieve the current occupancy figures and save them as the basis for a forecast model. In the background, a forecast model, e.g., LSTM, can also be trained by including further data such as weather and events. As soon as the model achieves solid results, the forecasts can be made available as an information service and integrated, for example, into the Bildungscampus app developed by the campus management.
With the information provided, the stakeholders on campus can directly switch to surrounding car parks in case of high occupancy. This avoids unnecessary congestion in the car park. In addition, new utilisation concepts for vacant spaces could be developed based on the precise analysis of parking space occupancy.
The solution can be transferred to other car parks and help municipalities with data-supported parking management and space management.
Other fields of application
public parking areas
private parking areas